Scott S. Hampton

Probabilistic & Bayesian Methods · 2004

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Probabilistic & Bayesian Methods — 5 citations into it

Whom Scott S. Hampton trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Radford M. Neal

Who trusts Scott S. Hampton overall

1. Jascha Narain Sohl-Dickstein
2. Daniel Lévy
3. Mayur Mudigonda
4. A. Berger
5. Michael Robert DeWeese

Papers from Scott S. Hampton's perspective

Ordered by how strongly the researchers Scott S. Hampton trusts endorse each paper. Same corpus, a different order for every researcher.

1. Sampling from multimodal distributions using tempered transitions
2. Monte Carlo Sampling Methods Using Markov Chains and Their Applications
3. Hybrid Monte Carlo
4. A Direct Approach to Conformational Dynamics Based on Hybrid Monte Carlo
5. Molecular modelling: Principles and applications
6. Higher-order hybrid Monte Carlo algorithms.
7. Optimal scaling for various Metropolis-Hastings algorithms
8. On adaptive Markov chain Monte Carlo algorithms
9. Sampling-Based Approaches to Calculating Marginal Densities
10. Weak convergence and optimal scaling of random walk Metropolis algorithms

Their papers

• Shadow hybrid Monte Carlo: an efficient propagator in phase space of macromolecules (2004) — 104 citations